Abstract: A fast gradient-descent (FGD) method is proposed for far-field pattern synthesis of large antenna arrays. Compared with conventional gradient-descent (GD) methods for pattern synthesis where ...

They can’t guarantee future health, but they can tell you the trajectory you’re on. By Dana G. Smith Take a minute to consider the last decade of your life. What type of physical shape do you hope to ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

As modern computing becomes limited by energy consumption, there is growing interest in physical computing paradigms that can operate closer to fundamental thermodynamic limits. Thermodynamic ...

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Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. Donald Trump's Epstein problem keeps coming back Michael ...

Abstract: Distributed gradient descent algorithms have come to the fore in modern machine learning, especially in parallelizing the handling of large datasets that are distributed across several ...